Anti-GPR150 polyclonal antibody

Methylated promoter CpG islands (CGIs) can be used to find novel tumor-suppressor genes and disease markers. In this study, to identify promoter CGIs aberrantly methylated in human ovarian cancers, we performed a genome-wide screening for differentially methylated DNA fragments using methylation-sensitive-representational difference analysis (MS-RDA). MS-RDA isolated 185 DNA fragments specifically methylated in an ovarian cancer cell line (ES-2), compared with a normal human ovarian surface epithelial cell line (HOSE6-3), and 33 of them were derived from putative promoter CGIs. Ten ovarian cancer cell lines were analyzed by methylation-specific PCR, and seven (GPR150, LOC222171, PRTFDC1, LOC339210, ITGA8, C9orf64 and HOX1911) of the 33 CGIs were methylated in one or more of the cell lines. Their downstream genes were barely expressed in cell lines without unmethylated DNA molecules by quantitative reverse-transcription-PCR. Demethylation of methylated cell lines with 5-aza-2'-deoxycytidine restored expression of two genes (PRTFDC1 and C9orf64). In primary ovarian cancers, CGIs of GPR150 (in 4 of 15 cancers), ITGA8 (2/15), PRTFDC1 (1/15), and HOADII (1/15) were methylated. Silencing of PRTFDC1 was revealed here for the first time, and aberrant methylation of GPR150, ITGA8 and HOXD11 could be candidate tumor markers. (c) 2007 Elsevier Inc. All rights reserved.

Head and neck cancer (HNC) remains one of the most malignant tumors with a significantly high mortality. DNA methylation exerts a vital role in the prognosis of HNC. In this study, we try to screen abnormal differentialmethylation genes (DMGs) and pathways in Head-Neck Squamous Cell Carcinoma via integral bioinformatics analysis. Data of gene expression microarrays and gene methylation microarrays were obtained from the Cancer Genome Atlas database. AberrantDMGs were identified by the R Limma package. We conducted the Cox regression analysis to select the prognostic aberrant DMGs and site-specific methylation. Five aberrant DMGs were recognized that significantly correlated with overall survival. The prognostic model was constructed based on five DMGs (PAX9, STK33, GPR150, INSM1, and EPHX3). The five DMG models acted as prognostic biomarkers for HNC. The area under the curve based on the five DMGs predicting 5-year survival is 0.665. Moreover, the correlation between the DMGs/site-specific methylation and gene expression was also explored. The findings demonstrated that the five DMGs can be used as independent prognostic biomarkers for predicting the prognosis of patients with HNC. Our study might lay the groundwork for further mechanismexploration in HNC and may help identify diagnostic biomarkers for early stage HNC.